Kidney transplantation is an obvious candidate for value based purchasing initiatives, aimed at improving quality and reducing costs of kidney transplant care in the United States. There is wide variation in quality, a large, single payer (CMS), and high quality data uniquely suited for profiling kidney transplant center quality. Unfortunately, the potential for value based purchasing to increase quality and reduce costs is limited by a lack of good measures. With respect to quality, the simple outcome measures that are currently used, such as graft function and mortality, may not reliably reflect a hospitals true performance and may be difficult to interpret. An empirically derived composite measure may overcome these limitations, but such a measure has not yet been developed. With this proposal, we will develop a composite measure of quality for kidney transplantation. Completing this aim will require the development of novel techniques to assess transplant center quality, and we propose to use empirical Bayes methods to develop a composite measure of one-year graft function. In addition to identifying high quality hospitals, payers are, of course, interested in constraining costs. For this reason, a better understanding of the relationship between quality and costs is critical in optimizing quality measures for value-based purchasing strategies. Thus, in this proposal we will develop a better understanding of the relationship between quality and costs in kidney transplantation. Specifically, we will assess how our composite measure of transplant center quality relates to transplant center Medicare payments for kidney transplant care.